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How can AI/Machine-Learning accelerate the discovery of new biomedical insights with high therapeutic application potential?
Summary of the video
This interview features Eddie Moler, the VP of Data Science at Juvenile Therapeutics, discussing the role of AI and machine learning in the discovery of biologic therapeutics. Moler explains his background in science and technology, transitioning from quantitative physical science to biology and life science applications. He highlights the impact of cloud technology and AI/ML in accelerating the discovery of new biological phenomena and developing therapies for various diseases. Juvenile Therapeutics, an early-stage biopharma startup, focuses on leveraging stem cell biology to identify and develop new treatments based on naturally secreted proteins. Moler discusses how AI and machine learning contribute to accelerating the discovery of biomedical insights with high therapeutic potential. He emphasizes the automation of drug discovery processes and the analysis of complex biological data, such as genomics and proteomics. Moler also mentions the challenge of examining hundreds of thousands of proteins and the role of AI in identifying key factors and patterns. He discusses the proprietary nature of technology and methods used but acknowledges the importance of sharing discoveries for scientific credibility. Moler concludes by highlighting the need for domain expertise and continuous learning in this rapidly evolving field.
Eddie Moler has over 20 years of experience leading pharmaceutical and clinical diagnostics R&D, data-science/algorithm/software intensive platform development, gene-target and biomarker discovery and validation, establishing and scaling high-performing data-science & software teams, and collaboration management.
Previously, Eddie led Quest Diagnostics’ Bioinformatics organization, leading the development and launch of dozens of advanced clinical genomic diagnostic tests while more than quadrupling the size of the team across multiple sites. He has led clinical/biological research projects and the development of production-scale clinical and research platforms at Quest Diagnostics, GE Healthcare, Tethys Bioscience, Novartis, and the US Department of Energy.
Eddie has published over 50 peer-reviewed papers including clinical and molecular medicine, population health, and health economics, and has 7 issued patents on clinical risk algorithms, biomarkers, automated histopathology image analysis, drug targets, and discovery technology. Eddie received a PhD in Chemistry from UC Berkeley and a BS in Chemistry from Texas A&M University.